Abstract

This PEP proposes changing the syntax for declaring metaclasses,
and alters the semantics for how classes with metaclasses are
constructed.

Rationale

There are two rationales for this PEP, both of which are somewhat
subtle.
The primary reason for changing the way metaclasses work, is that
there are a number of interesting use cases that require the
metaclass to get involved earlier in the class construction process
than is currently possible. Currently, the metaclass mechanism is
essentially a post-processing step. With the advent of class
decorators, much of these post-processing chores can be taken over
by the decorator mechanism.
In particular, there is an important body of use cases where it
would be useful to preserve the order in which a class members are
declared. Ordinary Python objects store their members in a
dictionary, in which ordering is unimportant, and members are
accessed strictly by name. However, Python is often used to
interface with external systems in which the members are organized
according to an implicit ordering. Examples include declaration of C
structs; COM objects; Automatic translation of Python classes into
IDL or database schemas, such as used in an ORM; and so on.
In such cases, it would be useful for a Python programmer to specify
such ordering directly using the declaration order of class members.
Currently, such orderings must be specified explicitly, using some
other mechanism (see the ctypes module for an example.)
Unfortunately, the current method for declaring a metaclass does
not allow for this, since the ordering information has already been
lost by the time the metaclass comes into play. By allowing the
metaclass to get involved in the class construction process earlier,
the new system allows the ordering or other early artifacts of
construction to be preserved and examined.
There proposed metaclass mechanism also supports a number of other
interesting use cases beyond preserving the ordering of declarations.
One use case is to insert symbols into the namespace of the class
body which are only valid during class construction. An example of
this might be "field constructors", small functions that are used in
the creation of class members. Another interesting possibility is
supporting forward references, i.e. references to Python
symbols that are declared further down in the class body.
The other, weaker, rationale is purely cosmetic: The current method
for specifying a metaclass is by assignment to the special variable
__metaclass__, which is considered by some to be aesthetically less
than ideal. Others disagree strongly with that opinion. This PEP
will not address this issue, other than to note it, since aesthetic
debates cannot be resolved via logical proofs.

Specification

In the new model, the syntax for specifying a metaclass is via a
keyword argument in the list of base classes:
class Foo(base1, base2, metaclass=mymeta):
...
Additional keywords will also be allowed here, and will be passed to
the metaclass, as in the following example:
class Foo(base1, base2, metaclass=mymeta, private=True):
...
Note that this PEP makes no attempt to define what these other
keywords might be - that is up to metaclass implementors to
determine.
More generally, the parameter list passed to a class definition will
now support all of the features of a function call, meaning that you
can now use *args and **kwargs-style arguments in the class base
list:
class Foo(*bases, **kwds):
...

Invoking the Metaclass

In the current metaclass system, the metaclass object can be any
callable type. This does not change, however in order to fully
exploit all of the new features the metaclass will need to have an
extra attribute which is used during class pre-construction.
This attribute is named __prepare__, which is invoked as a function
before the evaluation of the class body. The __prepare__ function
takes two positional arguments, and an arbitrary number of keyword
arguments. The two positional arguments are:
'name' - the name of the class being created.
'bases' - the list of base classes.
The interpreter always tests for the existence of __prepare__ before
calling it; If it is not present, then a regular dictionary is used,
as illustrated in the following Python snippet.
def prepare_class(name, *bases, metaclass=None, **kwargs):
if metaclass is None:
metaclass = compute_default_metaclass(bases)
prepare = getattr(metaclass, '__prepare__', None)
if prepare is not None:
return prepare(name, bases, **kwargs)
else:
return dict()
The example above illustrates how the arguments to 'class' are
interpreted. The class name is the first argument, followed by
an arbitrary length list of base classes. After the base classes,
there may be one or more keyword arguments, one of which can be
'metaclass'. Note that the 'metaclass' argument is not included
in kwargs, since it is filtered out by the normal parameter
assignment algorithm. (Note also that 'metaclass' is a keyword-
only argument as per PEP 3102 [6].)
Even though __prepare__ is not required, the default metaclass
('type') implements it, for the convenience of subclasses calling
it via super().
__prepare__ returns a dictionary-like object which is used to store
the class member definitions during evaluation of the class body.
In other words, the class body is evaluated as a function block
(just like it is now), except that the local variables dictionary
is replaced by the dictionary returned from __prepare__. This
dictionary object can be a regular dictionary or a custom mapping
type.
This dictionary-like object is not required to support the full
dictionary interface. A dictionary which supports a limited set of
dictionary operations will restrict what kinds of actions can occur
during evaluation of the class body. A minimal implementation might
only support adding and retrieving values from the dictionary - most
class bodies will do no more than that during evaluation. For some
classes, it may be desirable to support deletion as well. Many
metaclasses will need to make a copy of this dictionary afterwards,
so iteration or other means for reading out the dictionary contents
may also be useful.
The __prepare__ method will most often be implemented as a class
method rather than an instance method because it is called before
the metaclass instance (i.e. the class itself) is created.
Once the class body has finished evaluating, the metaclass will be
called (as a callable) with the class dictionary, which is no
different from the current metaclass mechanism.
Typically, a metaclass will create a custom dictionary - either a
subclass of dict, or a wrapper around it - that will contain
additional properties that are set either before or during the
evaluation of the class body. Then in the second phase, the
metaclass can use these additional properties to further customize
the class.
An example would be a metaclass that uses information about the
ordering of member declarations to create a C struct. The metaclass
would provide a custom dictionary that simply keeps a record of the
order of insertions. This does not need to be a full 'ordered dict'
implementation, but rather just a Python list of (key,value) pairs
that is appended to for each insertion.
Note that in such a case, the metaclass would be required to deal
with the possibility of duplicate keys, but in most cases that is
trivial. The metaclass can use the first declaration, the last,
combine them in some fashion, or simply throw an exception. It's up
to the metaclass to decide how it wants to handle that case.

Example:

Here's a simple example of a metaclass which creates a list of
the names of all class members, in the order that they were
declared:
# The custom dictionary
class member_table(dict):
def __init__(self):
self.member_names = []
def __setitem__(self, key, value):
# if the key is not already defined, add to the
# list of keys.
if key not in self:
self.member_names.append(key)
# Call superclass
dict.__setitem__(self, key, value)
# The metaclass
class OrderedClass(type):
# The prepare function
@classmethod
def __prepare__(metacls, name, bases): # No keywords in this case
return member_table()
# The metaclass invocation
def __new__(cls, name, bases, classdict):
# Note that we replace the classdict with a regular
# dict before passing it to the superclass, so that we
# don't continue to record member names after the class
# has been created.
result = type.__new__(cls, name, bases, dict(classdict))
result.member_names = classdict.member_names
return result
class MyClass(metaclass=OrderedClass):
# method1 goes in array element 0
def method1(self):
pass
# method2 goes in array element 1
def method2(self):
pass

Sample Implementation:

Alternate Proposals

Josiah Carlson proposed using the name 'type' instead of
'metaclass', on the theory that what is really being specified is
the type of the type. While this is technically correct, it is also
confusing from the point of view of a programmer creating a new
class. From the application programmer's point of view, the 'type'
that they are interested in is the class that they are writing; the
type of that type is the metaclass.
There were some objections in the discussion to the 'two-phase'
creation process, where the metaclass is invoked twice, once to
create the class dictionary and once to 'finish' the class. Some
people felt that these two phases should be completely separate, in
that there ought to be separate syntax for specifying the custom
dict as for specifying the metaclass. However, in most cases, the
two will be intimately tied together, and the metaclass will most
likely have an intimate knowledge of the internal details of the
class dict. Requiring the programmer to insure that the correct dict
type and the correct metaclass type are used together creates an
additional and unneeded burden on the programmer.
Another good suggestion was to simply use an ordered dict for all
classes, and skip the whole 'custom dict' mechanism. This was based
on the observation that most use cases for a custom dict were for
the purposes of preserving order information. However, this idea has
several drawbacks, first because it means that an ordered dict
implementation would have to be added to the set of built-in types
in Python, and second because it would impose a slight speed (and
complexity) penalty on all class declarations. Later, several people
came up with ideas for use cases for custom dictionaries other
than preserving field orderings, so this idea was dropped.

Backwards Compatibility

It would be possible to leave the existing __metaclass__ syntax in
place. Alternatively, it would not be too difficult to modify the
syntax rules of the Py3K translation tool to convert from the old to
the new syntax.